Data-Driven Reform of Precision College English Teaching in the Era of Educational Digital Transformation

This study explores a big data-based precision teaching framework in college English, utilizing the U-Campus AI platform. A one-semester experiment with 66 freshmen incorporated real-time data collection, learning feedback, homework digitalization, error correction, and personalized learning. Results show the experimental class's CET-4 passing rate reached 70.96%, 14.73 % higher than that of the control group, with significant improvements in students' learning initiative and autonomy. Data from the web-based questionnaire reveal that up to 74.31% participants have a positive attitude toward this new teaching approach, recognizing its effectiveness in enhancing engagement and learning outcomes The findings of this study validate the benefits of the teaching framework which not only improves learning performance and student motivation, but also supports teachers' professional development and enables more personalized, data-driven teaching decisions. This offers valuable insights for foreign language teaching reform in higher education, as institutions increasingly utilize big data and AI technologies to deliver tailored, student-centered instruction that cultivates comprehensive growth and core competencies.